• The Journal of Information Technology
• /
• v.10 no.2
• /
• pp.1-9
• /
• 2007

This study analyzed major cities of Chung-cheong area in Korea, -Daejeon($36^{\circ}11'{\sim}36^{\circ}30'\;N$, $127^{\circ}15'{\sim}127{\circ}34'\;E$), Chungju($36^{\circ}54'{\sim}37{\circ}02'\;N$, $127^{\circ}52'{\sim}128^{\circ}02'\;E$), and Cheongju($36^{\circ}34'{\sim}36^{\circ}44'\;N$, $127^{\circ}22'{\sim}127^{\circ}34'\;E$)- their characteristics as a Information Site. The geology map, a summit level map, and a drainage network map are created and analyzed the Site. The results are as follows : First, the geology of these cities are related with the shapes and the characteristics of the inner basins. The relief of inner basin determines by the characteristics of the bedrocks. Second, the major cities are close to rivers and the size of the granite & alluvium area influences the relief energy of the urban areas. Finally, the drainage networks explains the process involved in forming the basin and development of urban area.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1015-1017
• /
• 2003

Recently, DGPS or RTK-GPS techniques enable us to use satellite based positioning systems with high accuracy. But in urban area, navigation systems suffer from problems such as signal blockage by high-rise buildings, multi-path problems, and so on. So we have to know numbers of visible satellites and quality of signals received at the ground level in urban area as accurate as possible. In this paper, we developed a simulation system called LoQAS [Location service Quality Assessment System, 2002, the University of Tokyo] which can simulate numbers of visible satellites and DOP values using accurate satellite orbital data and 3-D digital map. In this time, we evaluated this system and extended it to deal with reflected signals to assess multi-path problems.

• ETRI Journal
• /
• v.43 no.4
• /
• pp.594-602
• /
• 2021

Recently, quantitative and repetitive inspections of the old urban area were conducted because many structures exceed their designed lifetime. The health of a building can be validated from the condition of the outer wall, while the slant angle of the wall widely serves as an indicator of urban regeneration projects. Mostly, the inspector directly measures the inclination of the wall or partially uses 3D point measurements using a static light detection and ranging (LiDAR). These approaches are costly, time-consuming, and only limited space can be measured. Therefore, we propose a mobile mapping system and automatic slant map generation algorithm, configured to capture urban environments online. Additionally, we use the LiDAR-inertial mapping algorithm to construct raw point clouds with gravity information. The proposed method extracts walls from raw point clouds and measures the slant angle of walls accurately. The generated slant angle map is evaluated in indoor and outdoor environments, and the accuracy is compared with real tiltmeter measurements.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.29 no.6
• /
• pp.27-36
• /
• 2002

The objective of this study is to improve the quality of the atmospheric environment by incorporating the factors of meteorology and urban climate into the field of urban and environmental planning. To this end, we have conducted a study on CLIMATOP and the mapping of urban climate, which are basic data used to analyze changes in climatic factors and the stagnation and accumulation of air pollutants. In particular, we focused on understanding the formation and movement of cold fresh air and its influx into urban areas by measuring and analyzing climatic factors. As a study result, classification criteria far CLIMATOP and a urban climatic map were made. In addition, we analyzed a digital elevation model, climatic data, and isothermal curves. As a result, we identified the corridor through which cold fresh air moves. We also observed that the temperature of the fluxed cold fresh air increased as land use changed. When the results of this study are applied to urban re-development and re-building projects, which require preliminary environmental assessment and environmental impact assessment, the practice proposed by this study is expected to contribute to the natural purification of air pollution activating the movement of cold fresh air and its influx into urban areas.

• Journal of Construction Engineering and Project Management
• /
• v.2 no.1
• /
• pp.20-26
• /
• 2012

Urban regeneration is a large-scale program that must address challenges such as a significant number of involved projects, diverse participants and their conflicting objectives, and a long life span. In an effort to address these issues, the Interactive Electronic Technical Manual (IETM) is applied to urban regeneration in order to provide a guideline to enhance urban regeneration program management. Through a survey, three major functionalities required in the IETM are identified: process map provision, customized information delivery, and communication ability with other information systems. To achieve these functionalities, the development framework of the IETM and the associated technologies are examined.Its characteristics can be sum up ontology-driven metadata, user-oriented process map composition system and so on. Finally, the usage scenarios of the IETM are discussed.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.3
• /
• pp.83-98
• /
• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Journal of Korean Society of Water Science and Technology
• /
• v.26 no.6
• /
• pp.133-142
• /
• 2018

Increasing localized torrential rainfall caused by abnormal climate are making higher damage to human and property through urban inundation So The need of preventive measures is being highlighted. In this study, the methodology for calculating flood depth in domestic water map using an interpolation method in order to utilizing the results of flood analysis provided only in the form of a report is suggested. In the Incheon Metropolitan City S area as the test-bed, the flood depth was calculated using the interpolating the actual flood analysis by image and verification was performed. Verification results showed that the error rate was 5.2% for the maximum flooding depth, and that the water depth value was compared to 10 random points, which showed a difference of less than 0.030 m. Also, as the results of the flood analysis were presented in various ways, the flood depth was extracted from the image of the result of the flood analysis, which changed the presentation method, and then compared and analyzed. The results of this study could be available for the use of basic data from the research on the urban penetration of domestic consumption and for decision-making of policy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.25 no.6_1
• /
• pp.499-505
• /
• 2007

A method of improving the correctness and confidence in land use classification as well as urban spatial structure analysis of local governments using GIS and satellite imagery is suggested. This study also compares and analyzes LSAS (Land Suitability Assessment System) results using two approaches-LSAS with priority classification, and LSAS using standard estimation factors without priority classification. The conclusions that can be drawn from this study are as follows. First, a method of maintaining up-to-date local government data by updating the LSAS database using high-resolution satellite imagery is suggested. Second, to formulate a scientific and reasonable land use plan from the viewpoint of territory development and urban management, a method of simultaneously processing the two described approaches is suggested. Finally, LSAS was constructed by using varieties of land information such as the cadastral map, the digital topographic map, varieties of thematic maps, and official land price data, and expects to utilize urban management plan establishment widely and effectively through regular data updating and problem resolution of data accuracy.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.5
• /
• pp.436-443
• /
• 2011

Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.14-19
• /
• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.